Adverse Media — Negative News Sentiment
Search negative news related to merchant companies and relevant individuals, including crime, financial crime, corruption, insolvency and sanctions-related issues.
Adverse Media — Negative News Sentiment
Prototype page exposes input contracts, processing stages, structured outputs, quality controls, privacy controls, integration points, PoC questions and evidence needed before production acceptance.
Inputs
Processing Pipeline
Generate controlled name variants and business aliases.
Search licensed/approved local and international sources; record source provenance.
Score subject match using name, organization, location, role, dates and other allowed features.
Cluster syndicated articles and remove duplicate evidence.
Classify issue type, severity, allegation vs confirmed outcome, and recency.
Ambiguous or high-impact findings must be dispositioned by an analyst before final decision.
Structured Outputs
| # | Question to provider | Prototype status | Evidence / response expected |
|---|---|---|---|
| 1 | What media-source coverage is monitored and how real-time is the refresh? | PoC response | Provide source inventory, Indonesia/international coverage, refresh SLAs and licensing. |
| 2 | How does entity resolution reduce false positives for common names? | PoC response | Provide matching features, thresholds, test results and manual-review controls. |
| 3 | Is the solution integrated with PEP/sanctions screening and how are domestic lists handled? | PoC response | Show connectors, list-update process, matching logic and governance. |
| 4 | Is an audit trail and source reference available for each finding? | PoC response | Show evidence object and decision lineage. |
| 5 | How is Bahasa Indonesia content supported? | PoC response | Provide language benchmark and local-name/entity handling. |
High-impact matching
False-positive protection is critical because adverse-media errors can unfairly block onboarding.
Special / criminal data
Where processing involves criminal or other sensitive data, purpose, necessity, access and retention require stronger controls.
Allegation ≠ fact
UI must explicitly distinguish allegation, investigation, charge, judgment and sanction status.
Correction / dispute
Merchant can trigger review of incorrect identity matches or stale/incorrect evidence.
Illustrative structured output
Schema is intentionally explicit to support decision-engine integration, explainability and audit. Values are simulated.